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Machine Learning still comes under the domain of unchartered territories, and we are constantly learning the applications of this modern-day technology. It has enabled computer systems to learn progressively and analyze patterns in data to adjust their actions automatically.
Machine Learning algorithms have found widespread applications in healthcare, cybersecurity, data security, and the financial world. Even eCommerce portals such as Amazon and Flipkart are deploying cutting-edge Machine Learning capabilities to ascertain requirements and recommend products to their users.
It was in 2016 that YouTube, the largest video sharing and viewing platform integrated Machine Learning in its suggestions algorithm, and it was not until the previous year that creators realized what hit their viewing metrics.
How Is YouTube implementing Machine Learning And AI?
YouTube is leveraging Machine Learning and AI capabilities to recommend videos to its users. It deploys ML to identify the most relevant videos that have significant runtime and suggest the most relevant videos to the users.
Suppose you run a YouTube channel with thousands of subscribers and are pushing out content regularly that generates user engagement, great! But, if your channel has fewer subscribers now, good luck in getting your videos in user suggestions.
YouTube's new recommendation system incorporates neural networks that automatically identify the viewing pattern of users and sends out video suggestions based on these patterns. This is the magic of Machine Learning.
As a user, if you have ever watched an entire YouTube video and the next video that is auto-played based on the suggestion, you have already witnessed the new YouTube prediction algorithm that integrates neural networks and AI. This has resulted in a massive change in video editing methods that creators deploy to create videos to post on YouTube. This new creation strategy tailored as per YouTube’s algorithms promises an increased viewership and visibility of your videos.
How To Optimize YouTube Videos?
YouTube prioritizes videos that are optimized for the platform as they result in a higher runtime and more time spent by the users while watching suggested videos on the platform - YouTube rewards videos as per the watch time that they accumulate.
Watch time is the duration that viewers watch a video, as opposed to the videos that they click and then abandon. The watch time metric gives us a perfect glimpse of what users actually want from their videos.
YouTube prioritizes videos that can lead to a higher watch time by users and can lead to the strengthening the video watching session. Remember, the watch time of the video is a higher priority, rather than the number of clicks that the videos garner.
So, how to create videos that help you in ensuring that users watch your videos further than the
first click? Below are a few key steps that can help you to create highly optimized videos for YouTube.
1. Leverage The Power Of YouTube Analytics
YouTube analytics is your best friend when looking for audience-specific insights and provides a plethora of reports.
Analytics can help you in getting audience insights so that you can push out more viewer-oriented content. Moreover, analytics can also help you in identifying the key areas in your video strategy that may require improvements.
2. Use a proper thumbnail and an enticing title
Thumbnails and titles are probably the two main things that users see before clicking on your video. You can deploy the below methods to create an attractive first-look for your videos.
Thumbnails and an enticing tile can go a long way in audience attraction and will compel the viewers to click on the video.
3. Methods to ensure audience retention and viewership
You have done all the marketing, but how to ensure that viewers watch your videos? Below are a few steps that you can take to ensure higher audience retention and increase your viewership.
In addition to these factors, you also need to ensure that your video's metadata, such as title, tags, and description perfectly relate to the video. These also help YouTube in indexing your videos correctly and ensures maximum viewership.
YouTube’s machine learning algorithms have drastically affected the way video creators are sending out video content. Relevance is still a major driving factor, but watch time has now emerged as a much more important metric.
As a creator, if you want your videos to be successful and ensure massive reach, it is crucial that you analyze the workings of the YouTube Machine learning algorithm and create videos that are in-line with the optimization guidelines mentioned above.
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